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Stanislav Belyaev

Stanislav Belyaev

Engineering Leader at Microsoft

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> 18
years of experience
2 000+
engineers
700+
graduates
9/10
course rating
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Career

Building and scaling engineering teams since 2008 – from startups to enterprises with thousands of developers. At Microsoft, doubled build system productivity for 2,000+ engineers. Previously transformed processes for 600+ IT staff at Tochka Bank, cutting delivery times from weeks to days.

Teaching

Co-author and mentor of the IT Project Manager course at Yandex Practicum – 500+ students over three years. Trainer at Stratoplan with a 9/10 course rating. Three years teaching Project Management in IT at Ural Federal University.

mysummit.school

A platform where managers learn to use AI in practice. Concrete skills: from writing prompts and detecting hallucinations to measuring ROI of AI adoption. Text-based format with interactive assignments – learn at your own pace.

Latest articles

The Agent Instead of Chat: Data Analysis Without Copy-Paste
11 min

The Agent Instead of Chat: Data Analysis Without Copy-Paste

You have three data files: an activation funnel, A/B test results, and support tickets. The task – figure out why onboarding is underperforming. You open ChatGPT, upload the first file, ask your question. You get an answer. You upload the second file. ChatGPT asks: “Can you remind me of the context?” You upload the third. The context of the first file has already been pushed out.

Forty minutes later you have three separate conversations, none of which answer the original question. Because the question was one, and the data was in three places.

This isn’t a ChatGPT problem. It’s a problem of approach.

Make Weak Model Great Again: Can Prompting Fix a Weak AI Model?
6 min

Make Weak Model Great Again: Can Prompting Fix a Weak AI Model?

Every team has a ‘good enough’ model. Maybe it’s the one your company approved. Maybe it’s the one that runs locally because legal won’t let data leave the building. Maybe it’s the only option your country’s regulations allow.

In Russia, this is about to become very literal. In March 2026, the Ministry of Digital Development published a draft law on “trusted AI models.” If passed – enforcement is planned from September 2027 – government agencies and critical infrastructure will be limited to models from an approved registry. ChatGPT, Claude, and Gemini, which route data through foreign servers, could be restricted. Russian-made AI assistants would be pre-installed on devices by default.

The problem is that Russian models lag behind. In our study of 54 models, GigaChat scored 3.26 out of 5. GPT-5.4 scored 4.80. That’s a 32% gap.

If GigaChat is all Russian managers have, can smart prompting pull acceptable quality out of it?

Claude Code Costs $100/Month – OpenCode Does the Same Thing for Free
13 min

Claude Code Costs $100/Month – OpenCode Does the Same Thing for Free

In March 2026, Lenny Rachitsky published an article with a telling headline: “Everyone should be using Claude Code”. It went viral on LinkedIn and tech newsletters, picked up hundreds of thousands of views, and now every week a manager somewhere asks: how do I try this?

The answer is uncomfortable. The Anthropic Max subscription that unlocks Claude Code costs $100 per month. That’s $1,200 a year for a single tool – before you’ve even figured out whether it fits your workflow. And it locks you into a single vendor, a single model, and a pricing tier designed for power users, not for someone exploring whether AI agents are worth the investment.

There’s a direct alternative. OpenCode is an open-source project that does exactly the same thing, works with any model (including free ones), and takes 15 minutes to set up.

When AI Hurts Learning – and When It Doubles Results
10 min

When AI Hurts Learning – and When It Doubles Results

In March 2025 at SXSW EDU, strategic foresight advisor Sinead Bovell delivered a talk on AI and the future of education. No hype, no panic. But with two studies that change how you should think about AI’s role in learning.

First: a group of students who used ChatGPT without restrictions scored 17% worse than the control group working from a textbook. Second: a different group, where AI was deployed within a fully redesigned instructional system, outperformed a traditional lecture by a factor of two.

Same tool. Opposite outcomes. The difference is in the approach.

GigaChat Ultra Thinking: Thinks Longer – Answers Worse?
7 min

GigaChat Ultra Thinking: Thinks Longer – Answers Worse?

GigaChat Ultra Thinking takes longer to think and uses more compute. It solves management tasks 3.3% worse than the version without reasoning. This is not a bug or a fluke – it’s a pattern documented in academic papers over the past two years.

This week, Sber unveiled GigaChat Ultra – a new flagship model with a reasoning mode (Thinking). The model is available for free via web, mobile apps, and a Telegram bot. We immediately added both variants to our AI model research for managers: ran them through all 32 scenarios using our unified methodology, scored them with both LLM judges, and compared against the other 52 models.

Course program

Learn how to systematically master AI for management tasks

Course program